Buch, Englisch, 236 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 376 g
4th International Workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001. Revised Papers
Buch, Englisch, 236 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 376 g
Reihe: Lecture Notes in Artificial Intelligence
ISBN: 978-3-540-43793-2
Verlag: Springer Berlin Heidelberg
UniversityofPennsylvania,USA TimKovacs UniversityofBirmingham,UK PierLucaLanzi PolitecnicodiMilano,Italy RickL. Riolo UniversityofMichigan,USA OlivierSigaud AnimatLab-LIP6,France RobertE. Smith TheUniversityofTheWestofEngland,UK WolfgangStolzmann DaimlerChryslerAG,Germany KeikiTakadama ATRInternational,Japan StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA TableofContents ITheory BiasingExplorationinanAnticipatoryLearningClassi?erSystem. 3 MartinV. Butz An Incremental Multiplexer Problem and Its Uses in Classi?er System Research. 23 LawrenceDavis,ChunshengFu,StewartW. Wilson AMinimalModelofCommunicationforaMulti-agentClassi?erSystem. 32 ´ GillesEn´ee,CathyEscazut A Representation for Accuracy-Based Assessment of Classi?er System PredictionPerformance. 43 JohnH. Holmes ASelf-AdaptiveXCS. 57 JacobHurst,LarryBull TwoViewsofClassi?erSystems. 74 TimKovacs SocialSimulationUsingaMulti-agentModelBasedonClassi?erSystems: TheEmergenceofVacillatingBehaviourinthe“ElFarol”BarProblem. 88 LuisMiramontesHercog,TerenceC. Fogarty II Applications XCSandGALE:AComparativeStudyofTwoLearningClassi?erSystems onDataMining. 115 EsterBernad´o,XavierLlor`a,JosepM. Garrell APreliminaryInvestigationofModi?edXCSasaGenericDataMining Tool. 133 PhillipWilliamDixon,DavidW. Corne,MartinJohnOates ExplorationsinLCSModelsofStockTrading. 151 SoniaSchulenburg,PeterRoss On-LineApproachforLossReductioninElectricPowerDistribution NetworksUsingLearningClassi?erSystems. 181 Patr´?ciaAmˆancioVargas,ChristianoLyraFilho, FernandoJ. VonZuben VIII TableofContents CompactRulesetsfromXCSI. 197 StewartW. Wilson III Appendix AnAlgorithmicDescriptionofACS2. 211 MartinV. Butz,WolfgangStolzmann AuthorIndex. 231 BiasingExplorationinan AnticipatoryLearningClassi?erSystem MartinV. Butz DepartmentofCognitivePsychology,UniversityofWurz ¨ burg R¨ ontgenring11,97070Wurz ¨ burg,Germany butz@psychologie. uni-wuerzburg. de Abstract. Thechapterinvestigateshowmodelandbehaviorallearning can be improved in an anticipatory learning classi?er system by bi- ing exploration. First, theappliedsystemACS2isexplained. Next,an overviewoverthepossibilitiesofapplyingexplorationbiasesinanant- ipatory learning classi?er systemand speci?cally ACS2 is provided.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Interdisziplinäres Wissenschaften Wissenschaften: Allgemeines
- Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
Weitere Infos & Material
Theory.- Biasing Exploration in an Anticipatory Learning Classifier System.- An Incremental Multiplexer Problem and Its Uses in Classifier System Research.- A Minimal Model of Communication for a Multi-agent Classifier System.- A Representation for Accuracy-Based Assessment of Classifier System Prediction Performance.- A Self-Adaptive XCS.- Two Views of Classifier Systems.- Social Simulation Using a Multi-agent Model Based on Classifier Systems: The Emergence of Vacillating Behaviour in the “El Farol” Bar Problem.- Applications.- XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining.- A Preliminary Investigation of Modified XCS as a Generic Data Mining Tool.- Explorations in LCS Models of Stock Trading.- On-Line Approach for Loss Reduction in Electric Power Distribution Networks Using Learning Classifier Systems.- Compact Rulesets from XCSI.- An Algorithmic Description of ACS2.
